Search research articles

ABOUT JoVE

Overview Leadership Blog JoVE Help Center

AUTHORS

Publishing Process Editorial Board Scope & Policies Peer Review FAQ Submit

LIBRARIANS

Testimonials Subscriptions Access Resources Library Advisory Board FAQ

RESEARCH

JoVE Journal Methods Collections JoVE Encyclopedia of Experiments Archive

EDUCATION

JoVE Core JoVE Business JoVE Science Education JoVE Lab Manual Faculty Resource Center Faculty Site

Terms & Conditions of Use

Related Concept Videos

Phylogenetic Trees

Phylogenetic Trees

Phylogenetic trees come in many forms. It matters in which sequence the organisms are arranged from the bottom to the top of the tree, but the branches can rotate at their nodes without altering the information. The lines connecting individual nodes can be straight, angled, or even curved.

Protein Networks

Protein Networks

An organism can have thousands of different proteins, and these proteins must cooperate to ensure the health of an organism. Proteins bind to other proteins and form complexes to carry out their functions. Many proteins interact with multiple other proteins creating a complex network of protein interactions.
These interactions can be represented through maps depicting protein-protein interaction networks, represented as nodes and edges. Nodes are circles that are representative of a protein,...

Protein Networks

Protein Networks

Network Covalent Solids

Network Covalent Solids

Network covalent solids contain a three-dimensional network of covalently bonded atoms as found in the crystal structures of nonmetals like diamond, graphite, silicon, and some covalent compounds, such as silicon dioxide (sand) and silicon carbide (carborundum, the abrasive on sandpaper). Many minerals have networks of covalent bonds.
To break or to melt a covalent network solid, covalent bonds must be broken. Because covalent bonds are relatively strong, covalent network solids are typically...

Network Function of a Circuit

Network Function of a Circuit

Frequency response analysis in electrical circuits provides vital insights into a circuit's behavior as the frequency of the input signal changes. The transfer function, a mathematical tool, is instrumental in understanding this behavior. It defines the relationship between phasor output and input and comes in four types: voltage gain, current gain, transfer impedance, and transfer admittance. The critical components of the transfer function are the poles and zeros.

Sequence Networks of Rotating Machines

Sequence Networks of Rotating Machines

A Y-connected synchronous generator, grounded through a neutral impedance, is designed to produce balanced internal phase voltages with only positive-sequence components. The generator's sequence networks include a source voltage that is exclusively in the positive-sequence network. The sequence components of line-to-ground voltages at the generator terminals illustrate this configuration.
Zero-sequence current induces a voltage drop across the generator's neutral impedance and other...

You might also read

Related Articles

Articles linked to this work by shared authors, journal, and citation graph.

Sort by

Same author

PCR-based species identification tools for wireworms (Coleoptera: Elateridae) of economic importance in Canada.

Pest management science·2026

Same author

Graphylo Var: Predicting the impact of non-coding variants using a multi-species sequence model.

Bioinformatics (Oxford, England)·2026

Same author

Tree Killer, Qu'est-ce Que C'est? Insights From Forest Pathogen Genomes.

Annual review of phytopathology·2026

Same author

H3K27me3 spreading organizes canonical PRC1 chromatin architecture to regulate developmental programs.

Nature genetics·2026

Same author

Telomere-to-telomere assembly detects genomic diversity in Canadian strains of Borrelia burgdorferi.

Cell reports·2026

Same author

A multivariate approach to identify association between peripheral blood DNA methylation and cerebrospinal fluid biomarkers of Alzheimer disease.

Scientific reports·2025

Same journal

3DICE: Interpretable 3D Cross-Modal Learning for Drug-Target Interaction Prediction and Large-Scale Drug Discovery.

Bioinformatics (Oxford, England)·2026

Same journal

KASSPer: Kinase Active Site Structure Prediction using Protein and Ligand Language Models and Its Application to Virtual Screening.

Bioinformatics (Oxford, England)·2026

Same journal

IDR searcher: a search engine solution for public image resources.

Bioinformatics (Oxford, England)·2026

Same journal

KCFtools: Rapid alignment-free method for introgression screening and GWAS using k-mer profiles.

Bioinformatics (Oxford, England)·2026

Same journal

Meta2DB: Curated shotgun metagenomic feature sets and metadata for health state prediction.

Bioinformatics (Oxford, England)·2026

Same journal

conMItion: an R package adjusting confounding factors for associations in multi-omics.

Bioinformatics (Oxford, England)·2026

See all related articles

Search research articles

Related Experiment Video

Updated: Jan 23, 2026

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Mycorrhiza: genotype assignment using phylogenetic networks.

Jeremy Georges-Filteau¹, Richard C Hamelin^2,3, Mathieu Blanchette¹

¹School of Computer Science, McGill University, Montreal, QC, Canada.

Bioinformatics (Oxford, England)

|June 15, 2019

Summary

This summary is machine-generated.

Mycorrhiza, a new machine learning method, accurately assigns individual genotypes to their populations using phylogenetic networks. This approach improves upon existing methods, especially for complex datasets, aiding biodiversity monitoring and conservation efforts.

More Related Videos

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Related Experiment Videos

Last Updated: Jan 23, 2026

A Practical Guide to Phylogenetics for Nonexperts

A Practical Guide to Phylogenetics for Nonexperts

Published on: February 5, 2014

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Using Phylogenetic Analysis to Investigate Eukaryotic Gene Origin

Published on: August 14, 2018

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Heuristic Mining of Hierarchical Genotypes and Accessory Genome Loci in Bacterial Populations

Published on: December 7, 2021

Area of Science:

Population Genetics
Bioinformatics
Machine Learning

Background:

The genotype assignment problem is crucial for wildlife forensics, invasive species detection, and biodiversity monitoring.
Existing methods often fail when assumptions like Hardy-Weinberg equilibrium are violated.

Purpose of the Study:

To introduce Mycorrhiza, a novel machine learning approach for genotype assignment.
To improve the accuracy and robustness of genotype assignment, particularly in challenging scenarios.

Main Methods:

Mycorrhiza utilizes phylogenetic networks to create features reflecting evolutionary relationships.
These features are then processed by a Random Forests classifier.
The approach was validated on diverse empirical and simulated datasets.

Main Results:

Mycorrhiza demonstrated superior classification accuracy compared to established methods like STRUCTURE and Admixture.
Significant performance gains were observed on datasets with high FST or deviations from Hardy-Weinberg equilibrium.
The method also accurately estimated mixture proportions.

Conclusions:

Mycorrhiza offers a powerful and accurate solution for the genotype assignment problem.
Its reliance on phylogenetic networks makes it robust to common violations of population genetic assumptions.
The open-source availability facilitates its adoption in ecological and conservation research.